Crowdsourced Transit predictions

When high-quality information provided by a transit agency isn’t available, Google uses aggregated crowdsourced data to predict public transit:

  • Realtime locations
  • Arrival and departure times
  • Crowd size

Live trip status for trains

Google predicts your train's live location, and when it will depart and arrive at your destination. 
Location history reports from users around the world are combined with train track locations to detect moving trains. The trains are matched to published schedules to predict when the trains will arrive at upcoming stations. This data is provided to Google Maps users in the form of realtime train locations and arrival and departure times.
Important: Live trip status for trains is currently only available in Manila, PH as a pilot.

Live traffic for buses

Google forecasts bus travel times by using a machine learning model that combines realtime car traffic forecasts with data about bus routes and stops. 

It’s not enough to simply calculate car traffic because buses navigate in a fundamentally different way than cars. For example, buses may:

  • Stop at bus stops
  • Take longer to accelerate, slow down, and turn 
  • Have special road privileges like dedicated bus lanes

This difference in movement is factored into the model to create accurate delay information tailored specifically for buses. Get more technical details on our Google AI blog.

Public transit crowd size

When you search for transit directions, Google predicts public transit crowd size.
Google predicts your vehicle’s crowding by seeking optional feedback from Google Maps users who have opted-in to share their contributions. Google sends notifications to users who have enabled notification and location permissions for Maps on their device, and signalled they are riding a transit vehicle. 
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